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At least 775 records · Page 43

Photogrammetry: Develop methods for detecting deviations from expected geometry of components in a glovebox environment (Lawrence Livermore National Laboratory Aging and Lifetimes Program FY23, Milestone 8651, Grading Criterion #4)

Measurements in glovebox environments are challenging to conduct. Currently deployed techniques are time consuming and provide limited information. These limitations make current disposition and future assessments of products challenging. In FY23 we developed methods for detecting deviations of components in a glovebox environment that address these shortcomings by rapidly collecting information-dense measurements. Conducted tests demonstrate that camera pose (position and orientation) can be derived for images utilized in the photogrammetry process. This information, in conjunction with common image processing techniques, enables automated detection and size estimation of surface features. First, image processing is used to identify marks, or localized regions, that standout from the surrounding area. Then, the physical size of the region can be estimated because scale can be determined for photogrammetry images. Development of this methods shows that photogrammetry can identify measurable deviations from expected geometries. Although measurement error when using this technique through a glovebox window still needs to be reduced, this capability shows promise for eliminating or reducing the use of tedious manual measurements.

42 ENGINEERING↗

SULI Deliverables Using: Python-B1500 [Slides]

A new electrical setup for testing ECRAM devices is described in this presentation. This presentation details the background of ECRAM devices, how the B1500 is used to program ECRAM devices, and the python GUI that was created for controlling the B1500. ECRAM devices are a form of non-volatile memory. The stored data is the resistance between two of the terminals on the device. Using only the B1500, the ECRAM devices can be programmed and the state read out. This creates a simple, logical testing setup. The overall setup was successful, ECRAM devices could easily be programmed and measured. However, there is still room for improvement. Specifically, in the creation of an automated “Program” feature and a “Data Collection” feature. These features will require additional advances in the understanding of ECRAM devices but will greatly automate and improve the current data collection and application of ECRAM devices.

42 ENGINEERING↗

Super Conducting REBCO Cable Wrapper

Future upgrades to CERN particle accelerator magnets require flat, high-temperature superconducting cables, created by wrapping brittle REBCO tape around a Rutherford copper core. Because current manual wrapping processes are time-consuming and prone to damaging the delicate ceramic tape, our team was tasked with automating the fabrication. We developed a modular, wrapping machine featuring adjustment for repeatable 10°to 45° wrap angles and a precise magnetic tensioning mechanism. While full-scale testing is pending final machined parts, our 3D-printed prototype successfully validates the system’s motion and sets the stage for future testing.

Gillen, Kameron [Northern Illinois U.]↗

Transient events in archival very large array observations of the galactic center

The Galactic center has some of the highest stellar densities in the Galaxy and a range of interstellar scattering properties, which may aid in the detection of new radio-selected transient events. Here, we describe a search for radio transients in the Galactic center, using over 200 hr of archival data from the Very Large Array at 5 and 8.4 GHz. Every observation of Sgr A* from 1985 to 2005 has been searched using an automated processing and detection pipeline sensitive to transients with timescales between 30 s and 5 minutes with a typical detection threshold of ∼100 mJy. Eight possible candidates pass tests to filter false-positives from radio-frequency interference, calibration errors, and imaging artifacts. Two events are identified as promising candidates based on the smoothness of their light curves. Despite the high quality of their light curves, these detections remain suspect due to evidence of incomplete subtraction of the complex structure in the Galactic center, and apparent contingency of one detection on reduction routines. Events of this intensity (∼100 mJy) and duration (∼100 s) are not obviously associated with known astrophysical sources, and no counterparts are found in data at other wavelengths. We consider potential sources, including Galactic center pulsars, dwarf stars, sources like GCRT J1745−3009, and bursts from X-ray binaries. None can fully explain the observed transients, suggesting either a new astrophysical source or a subtle imaging artifact. More sensitive multiwavelength studies are necessary to characterize these events, which, if real, occur with a rate of 14{sub −12}{sup +32} hr{sup −1} deg{sup −2} in the Galactic center.

79 ASTRONOMY AND ASTROPHYSICS↗

Understanding the Impacts of Stellar Companions on Planet Formation and Evolution: A Survey of Stellar and Planetary Companions within 25 pc

We explore the impact of outer stellar companions on the occurrence rate of giant planets detected with radial velocities. We searched for stellar and planetary companions to a volume-limited sample of solar-type stars within 25 pc. Using adaptive optics imaging observations from the Lick 3 m and Palomar 200″ Telescopes, we characterized the multiplicity of our sample stars, down to the bottom of the main sequence. With these data, we confirm field star multiplicity statistics from previous surveys. We additionally combined three decades of radial velocity (RV) data from the California Planet Search with newly collected RV data from Keck/HIRES and the Automated Planet Finder/Levy Spectrometer to search for planetary companions in these same systems. Using an updated catalog of both stellar and planetary companions, as well as detailed injection/recovery tests to determine our sensitivity and completeness, we measured the occurrence rate of planets among the single- and multiple-star systems. We found that planets with masses in the range of 0.1–10 M {sub J} and with semimajor axes of 0.1–10 au have an occurrence rate of 0.18{sub −0.03}{sup +0.04} planets per star when they orbit single stars and an occurrence rate of 0.12 ± 0.04 planets per star when they orbit a star in a binary system. Breaking the sample down by the binary separation, we found that only one planet-hosting binary system had a binary separation <100 au, and none had a separation <50 au. These numbers yielded planet occurrence rates of 0.20{sub −0.06}{sup +0.07} planets per star for binaries with separation a {sub B} > 100 au and 0.04{sub −0.02}{sup +0.04} planets per star for binaries with separation a {sub B} < 100 au. The similarity in the planet occurrence rate around single stars and wide primaries implies that wide binary systems should actually host more planets than single-star systems, since they have more potential host stars. We estimated a system-wide planet occurrence rate of 0.3 planets per wide binary system for binaries with separations a {sub B} > 100 au. Finally, we found evidence that giant planets in binary systems have a different semimajor-axis distribution than their counterparts in single-star systems. The planets in the single-star sample had a significantly higher occurrence rate outside of 1 au than inside 1 au by nearly 4σ, in line with expectations that giant planets are most common near the snow line. However, the planets in the wide binary systems did not follow this distribution, but rather had equivalent occurrence rates interior and exterior to 1 au. This may point to binary-mediated planet migration acting on our sample, even in binaries wider than 100 au.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Impact of collection container material and holding times on sample integrity for mercury and methylmercury in water

Mercury (Hg) and methylmercury (MeHg) concentrations in streamwater can vary on short timescales (hourly or less) during storm flow and on a diel cycle; the frequency and timing of sampling required to accurately characterize these dynamics may be difficult to accomplish manually. Automated sampling can assist in sample collection; however use has been limited for Hg and MeHg analysis due to stability concerns of trace concentrations during extended storage times. We examined the viability of using automated samplers with disposable low-density polyethylene (LDPE) sample bags to collect industrially contaminated streamwater for unfiltered and filtered Hg and MeHg analysis. Specifically we investigated the effect of holding times ranging from hours to days on streamwater collected during baseflow and storm flow. Unfiltered and filtered Hg and MeHg concentrations decreased with increases in time prior to sample processing; holding times of 24 hours or less resulted in concentration changes (mean 11 7% different) similar to variability in duplicates collected manually during analogous field conditions (mean 7 10% different). Comparisons of samples collected with manual and automated techniques throughout a year for a wide range of stream conditions were also found to be similar to differences observed between duplicate grab samples. These results demonstrate automated sampling into LDPE bags with holding times of 24 hours or less can be effectively used to collect streamwater for Hg and MeHg analysis, and encourage the testing of these materials and methods for implementation in other aqueous systems where high-frequency sampling is warranted.

holding time↗

Antarctic ice sheet model comparison with uncurated geological constraints shows that higher spatial resolution improves deglacial reconstructions

Accurately reconstructing past changes to the shape and volume of the Antarctic ice sheet relies on the use of physically based and thus internally consistent ice sheet modeling, benchmarked against spatially limited geologic data. The challenge in model benchmarking against geologic data is diagnosing whether model-data misfits are the result of an inadequate model, inherently noisy or biased geologic data, and/or incorrect association between modeled quantities and geologic observations. In this work we address this challenge by (i) the development and use of a new model-data evaluation framework applied to an uncurated data set of geologic constraints, and (ii) nested high-spatial-resolution modeling designed to test the hypothesis that model resolution is an important limitation in matching geologic data. While previous approaches to model benchmarking employed highly curated datasets, our approach applies an automated screening and quality control algorithm to an uncurated public dataset of geochronological observations (specifically, cosmogenic-nuclide exposure-age measurements from glacial deposits in ice-free areas). This optimizes data utilization by including more geological constraints, reduces potential interpretive bias, and allows unsupervised assimilation of new data as they are collected. We also incorporate a nested model framework in which high-resolution domains are downscaled from a continent-wide ice sheet model. We highlight the application of this framework by applying these methods to a small ensemble of deglacial ice-sheet model simulations, and demonstrate that the nested approach improves the ability of model simulations to match exposure age data collected from areas of complex topography and ice flow. We develop a range of diagnostic model-data comparison metrics to provide more insight into model performance than possible from a single-valued misfit statistic, showing that different metrics capture different aspects of ice sheet deflation.

Geosciences↗

Microfluidic-Based Sample Chips for Radioactive Solutions

Historical nuclear fuel cycle process sampling techniques required sample volumes ranging in the tens of milliliters. The radiation levels experienced by analytical personnel and equipment, in addition to the waste volumes generated from analysis of these samples, have been significant. These sample volumes also impacted accountability inventories of required analytes during process operations. To mitigate radiation dose and other issues associated with the historically larger sample volumes, a microcapillary sample chip was chosen for further investigation. The ability to obtain microliter volume samples coupled with a remote automated means of sample loading, tracking, and transporting to the analytical instrument would greatly improve analytical efficiency while reducing both personnel exposure and radioactive waste volumes. Sample chip testing was completed to determine the accuracy, repeatability, and issues associated with the use of microfluidic sample chips used to supply µL sample volumes of lanthanide analytes dissolved in nitric acid for introduction to an analytical instrument for elemental analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Extraction and Analysis of Time Series Data from Building Automation Systems Using Large Language Models

Semantic schemas like Haystack 4, Brick and ASHRAE standard 223 enable the structured, standardized, and machine-readable representation of building data, facilitating interoperability, data integration, and advanced analytics. However, extracting information from these models requires specialized expertise in SPARQL and other programming languages, skills that are not commonly found among building professionals. Recent advancements in Large Language Models (LLMs), such as ChatGPT, enable the construction of queries using natural language, making it easier for individuals to interact with these systems in a manner that resembles everyday speech. However, these methods have not yet been tested on building semantic ontologies. This paper introduces a novel workflow and tool for enabling users to ask questions about a specific building's data, using natural language and receive answers automatically generated by GPT-4o. Our approach integrates semantic ontologies with advanced LLM capabilities to automate three critical steps: (1) generating SPARQL queries to retrieve time series references from ontological models, (2) extracting the corresponding time series data from the Building Automation System, and (3) performing computations and visualizations tailored to the user's query. The proposed method simplifies access to BAS data, allowing both domain experts and non-specialists to conduct sophisticated analyses without needing extensive technical knowledge of semantic web technologies. By demonstrating this pipeline, we facilitate more accessible and scalable data-driven decision-making in building operations and management.

Mulayim, Ozan Baris↗

Extraction and Analysis of Time Series Data from Building Automation Systems Using Large Language Models

Semantic schemas like Haystack 4, Brick and ASHRAE standard 223 enable the structured, standardized, and machine-readable representation of building data, facilitating interoperability, data integration, and advanced analytics. However, extracting information from these models requires specialized expertise in SPARQL and other programming languages, skills that are not commonly found among building professionals. Recent advancements in Large Language Models (LLMs), such as ChatGPT, enable the construction of queries using natural language, making it easier for individuals to interact with these systems in a manner that resembles everyday speech. However, these methods have not yet been tested on building semantic ontologies. This paper introduces a novel workflow and tool for enabling users to ask questions about a specific building's data, using natural language and receive answers automatically generated by GPT-4o. Our approach integrates semantic ontologies with advanced LLM capabilities to automate three critical steps: (1) generating SPARQL queries to retrieve time series references from ontological models, (2) extracting the corresponding time series data from the Building Automation System, and (3) performing computations and visualizations tailored to the user's query. The proposed method simplifies access to BAS data, allowing both domain experts and non-specialists to conduct sophisticated analyses without needing extensive technical knowledge of semantic web technologies. By demonstrating this pipeline, we facilitate more accessible and scalable data-driven decision-making in building operations and management.

Mulayim, Ozan Baris↗

Perspectives for self-driving labs in synthetic biology

Self-driving labs (SDLs) combine fully automated experiments and data collection with artificial intelligence (AI) and control algorithms that decide not only the set of parameters for the next experiment, but also potentially which scientific hypotheses to test. Taken to their ultimate expression, SDLs could usher a new paradigm of scientific research, where the world is probed, interpreted, and explained by machines for human benefit. Whereas there are functioning SDLs in the fields of chemistry and materials science, we contend that synthetic biology provides a unique opportunity since the genome provides a single, easily accessible, target for affecting the incredibly wide repertoire of biological cell behavior. Since they can provide large amounts of high-quality data, SDLs can be a platform for AI to develop approaches to systematically convert data into scientific knowledge systems. These knowledge systems can be used both to understand the biological world and to design bioengineered systems to fit a desired specification (inverse design). However, the level of investment required for the creation of biological SDLs is only warranted if directed towards solving difficult and enabling biological questions. Here, we discuss challenges and opportunities in creating SDLs for synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗

Automated Segmentation of Twin Boundaries in TRISO Silicon Carbide Using Deep Neural Networks

Coated particle fuels, such as the tristructural isotropic (TRISO) fuel particle, are essential for high-temperature gas reactor (HTGR) applications due to their efficiency and stability under normal and off-normal conditions. However, widespread commercialization and deployment of this technology for next-generation nuclear applications require robust quality assurance and quality control (QA/QC) methods linking fabrication, properties, and performance. Of the many important metrics for TRISO QA/QC, quantification of the silicon carbide (SiC) microstructure is critical because it correlates with fission product retention during irradiation. Previous work has shown extensive twinning of the SiC microstructure, which strongly affects microstructural metrics; however, twin grain boundaries are not expected play a significant role in fission product diffusion. This report summarizes the initial development, training, and testing of a machine learning image processing algorithm to detect twin grain boundaries in a backscattered electron image, which can be removed so that microstructural metrics can be recalculated for legacy data. Further development and deployment of this model will provide automated, scalable improvement of potential QA/QC methods for the SiC layer of TRISO particles.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Flat and Level Analysis Tool (FLAT) for real-time automated segmentation and analysis of concrete slab point clouds

In the United States, the flatness and levelness of concrete floors during construction is traditionally specified by a maximum allowable gap under a 3 meter straightedge. However, the straightedge method is inexact and rarely representative of the entire floor since the technician is free to choose any location on the floor to perform the measurement. In cases requiring a higher degree of precision and repeatability, concrete floor flatness and levelness can be measured using the standard test method ASTM E1155. With the recent introduction of advanced surveying instruments such as robotic theodolites and terrestrial laser scanners (TLS), the means now exist to modernize and expedite the measurement of floor flatness and levelness. This paper details the development and demonstration of a digital tool, named the Flat and Level Analysis Tool (FLAT), to automate and expedite the segmentation and analysis of flatness and levelness from dense point cloud data of concrete floor slabs. Segmentation algorithms were developed using unsupervised machine learning to extract the set of points belonging to the concrete floor slab from a full 360 scan of a construction site. After segmentation, automated analysis algorithms report the results according to the standard method. The developed algorithms were demonstrated on a dense point cloud captured from a concrete slab-on-grade at a construction site. Results show that the digital tool can quickly provide estimates for floor flatness and levelness with minimal human involvement with comparable accuracy to manual methods.

Hayes, Nolan↗

Coronary artery analysis: Computer-assisted selection of best-quality segments in multiple-phase coronary CT angiography

Purpose: The authors are developing an automated method to identify the best-quality coronary arterial segment from multiple-phase coronary CT angiography (cCTA) acquisitions, which may be used by either interpreting physicians or computer-aided detection systems to optimally and efficiently utilize the diagnostic information available in multiple-phase cCTA for the detection of coronary artery disease. Methods: After initialization with a manually identified seed point, each coronary artery tree is automatically extracted from multiple cCTA phases using our multiscale coronary artery response enhancement and 3D rolling balloon region growing vessel segmentation and tracking method. The coronary artery trees from multiple phases are then aligned by a global registration using an affine transformation with quadratic terms and nonlinear simplex optimization, followed by a local registration using a cubic B-spline method with fast localized optimization. The corresponding coronary arteries among the available phases are identified using a recursive coronary segment matching method. Each of the identified vessel segments is transformed by the curved planar reformation (CPR) method. Four features are extracted from each corresponding segment as quality indicators in the original computed tomography volume and the straightened CPR volume, and each quality indicator is used as a voting classifier for the arterial segment. A weighted voting ensemble (WVE) classifier is designed to combine the votes of the four voting classifiers for each corresponding segment. The segment with the highest WVE vote is then selected as the best-quality segment. In this study, the training and test sets consisted of 6 and 20 cCTA cases, respectively, each with 6 phases, containing a total of 156 cCTA volumes and 312 coronary artery trees. An observer preference study was also conducted with one expert cardiothoracic radiologist and four nonradiologist readers to visually rank vessel segment quality. The performance of our automated method was evaluated by comparing the automatically identified best-quality segments identified by the computer to those selected by the observers. Results: For the 20 test cases, 254 groups of corresponding vessel segments were identified after multiple phase registration and recursive matching. The AI-BQ segments agreed with the radiologist’s top 2 ranked segments in 78.3% of the 254 groups (Cohen’s kappa 0.60), and with the 4 nonradiologist observers in 76.8%, 84.3%, 83.9%, and 85.8% of the 254 groups. In addition, 89.4% of the AI-BQ segments agreed with at least two observers’ top 2 rankings, and 96.5% agreed with at least one observer’s top 2 rankings. In comparison, agreement between the four observers’ top ranked segment and the radiologist’s top 2 ranked segments were 79.9%, 80.7%, 82.3%, and 76.8%, respectively, with kappa values ranging from 0.56 to 0.68. Conclusions: The performance of our automated method for selecting the best-quality coronary segments from a multiple-phase cCTA acquisition was comparable to the selection made by human observers. This study demonstrates the potential usefulness of the automated method in clinical practice, enabling interpreting physicians to fully utilize the best available information in cCTA for diagnosis of coronary disease, without requiring manual search through the multiple phases and minimizing the variability in image phase selection for evaluation of coronary artery segments across the diversity of human readers with variations in expertise.

61 RADIATION PROTECTION AND DOSIMETRY↗

Development of NDE/NDT Tools for High-Volume & High-Speed Inspection of CFRP Structures in Automotive Manufacturing

Main advantages of the air-coupled ultrasound testing (ACUT) and electromagnetic testing (EMT) techniques for NDE of CFRP composites were non-contact sensing, scalability for high-speed inspection, cost-effectiveness, and non-hazardous operation. Despite these advantages, no systems that would satisfy the project requirements were commercially available. Hence, one of the major efforts of the Michigan State University (MSU) team at the initial stage of the project was to close this technological gap by developing, optimizing, and validating array sensors that would provide sufficient sensitivity, spatial coverage, and resolution for robust defect detection. Optimization of the ACUT and EMT sensor designs was performed using experimentally validated finite element models. Initial experiments using array probes were conducted on relatively flat CFRP samples. In parallel, the MSU team designed and assembled a portable platform with two robotic arms. The robots were equipped with newly designed sensors that enabled high-speed NDE of curved CFRP parts. Presently, the developed robotic platform can be used as a demo/template NDE system, which is easily adaptable to manufacturing environments and in-line NDE. The ACUT NDE system developed by the MSU team used a high-power 4-channel pulser receiver for parallel data acquisition. The array probes were designed by stacking commercially available ACUT transducers, which operated in the frequency range between 100 kHz and 500 kHz. MSU optimized the excitation procedure and developed wave focusing cones so as to reduce the crosstalk between the transducers and to provide higher pulse repletion frequency (PRF). The through-transmission (TT) and single-side access (SSA) inspection modes were successfully implemented. In the TT-ACUT, structural defects in CFRP were detected by passing ultrasonic waves through the test part. Hence, the ACUT transmitters and receivers needed to be placed on the opposite sides of the test part. In the SSA-ACUT, guided waves (GW) were excited in the test part using the transmitters and were sensed by the receivers from the same side. Multi-channel TT-ACUT and SSA-ACUT provided high-speed NDE, and were successfully validated on CFRP test samples with interlaminar delaminations and other embedded defects The EM techniques developed by the MSU team included: 1) eddy current testing (ECT), 2) capacitive imaging (CI) and hybrid dual-mode imaging. In ECT, structural damage was detected in CFRP using coils sensor arrays. In ECT, the excitation magnetic field is generated by passing an alternating current through a coil, which is placed above the test sample. The excitation field penetrates the conductive sample and induces the eddy currents in its transect. In turn, the eddy currents generate the reaction field, which affects the total field sensed by a coil. Hence, the presence of structural flaws will alter the eddy current flow and the picked-up signal. ECT is mostly sensitive to local changes of the electric conductivity of the test sample, and CFRPs are mostly conductive in the direction of carbon fibers. Hence, ECT was well suited for the detection of fiber damage/fiber irregularities. The MSU team developed printed circuit boards (PCB) with coil sensor arrays optimized for NDE of CFRP. Unlike most commercial probes designed for ECT of metallic structures, the MSU array probes were designed for operation in [1-10] MHz frequency range, which was optimal for low-conductive CFRP. Multiple sensing topologies (coil groups excitation/sensing arrangements) were implemented and successfully validated. Capacitive Imaging (CI) technique developed by MSU was complementary to ECT. In contrast to ECT, which was sensitive to local changes of the electrical conductivity, the CI was sensitive to local changes of the dielectric constant. Therefore, CI could provide information about matrix damage/matrix irregularities in CFRP. The MSU CI sensor arrays were made of multiple circular or rectangular open-plate capacitors printed on PCB. Sensors of this type are not commercially available. In addition to ECT and CI, the MSU team developed a hybrid (dual-mode) inductive/capacitive measurement technique that synergistically combined the benefits of inductive and capacitive sensing for rapid NDE of fiber reinforced polymer (FRP) composite structures. Fiber damage and fiber irregularities in FRPs were detected by configuring hybrid sensors as coil sensors. Similarly, matrix damage, matrix irregularities and interlaminar delaminations were detected by configuring hybrid sensors as capacitive sensors. ECT and CI were performed sequentially by means of electronic switching. Hence, eliminating the need for mounting two separate sensor arrays on the probe. Portable robotic platform was developed by MSU for multi-technique high-speed NDE of CFRP test parts. The platform had two 6-axis robots, which enabled inspection of curved parts in approximately a 6×6×6 ft 3 active scan area. On the software side, the MSU team integrated scripts for NDE hardware control with scripts for robot motion control. MSU also implemented automated path planning for the robots, reconstruction of part’s surfaces via stereovision, 3D rendering of inspection data, and image processing algorithms for enhanced defect detection. Automotive composite parts manufactured by Plasan Composites from Phase I were used to validate the ACUT and EMT techniques on representative testbeds. Among those parts were three X-braces for a Dodge Viper, one composite calibration plaque with known defects at known locations, and four other test sections, including sections from a front splitter, a corner section from a composite hood, and a high-pressure RTM panel made using non crimp fabric. Other test samples included CFRP and GFRP calibration plates with fiber/matrix defects fabricated at MSU/CVRC.

36 MATERIALS SCIENCE↗

A Three–Dimensional Nanoscale View of Electrocatalyst Degradation in Hydrogen Fuel Cells

The loss of platinum (Pt) electrochemically active surface area (ECSA) is a critical degradation mode that often becomes a limiting factor for heavy-duty proton exchange membrane fuel cell vehicles. High surface area carbon supports have been shown to improve Pt dispersion and limit detrimental ionomer-electrocatalyst interactions due to their large interior pore volume. Here, in this work, using automated scanning transmission electron tomography, the degradation of nanoparticles located on the interior versus exterior surfaces of the carbon support is compared following a catalyst-specific accelerated stress test (AST) of 90,000 voltage cycles between 0.6 V to 0.95 V. The results reveal a notable increase in median particle size for both interior and exterior Pt catalyst particles, with a slightly higher increase in particle size distribution and loss of specific surface area for the particles located on the exterior carbon surface. The fraction of Pt nanoparticles that reside within the interior of the carbon support also increased following the AST test, accompanied by evidence of an increase in average carbon mesopore size. Here, the results shed light on the degradation mechanisms affecting electrochemical properties and the enhanced particle accessibility at lower relative humidity.

08 HYDROGEN↗

A method for distinguishing between propagons, diffusions, and locons

The majority of intuition on phonon transport has been derived from studies of homogenous crystalline solids, where the atomic composition and structure are periodic. For this specific class of materials, the solutions to the equations of motions for the atoms (in the harmonic limit) result in plane wave modulated velocity fields for the normal modes of vibration. However, it has been known for several decades that whenever a system lacks periodicity, either compositional or structural, the normal modes of vibration can still be determined (in the harmonic limit), but the solutions take on different characteristics and many modes may not be plane wave modulated. Previous work has classified the types of vibrations into three primary categories, namely, propagons, diffusions, and locons. One can use the participation ratio to distinguish locons, from propagons and diffusons, which measures the extent to which a mode is localized. However, distinguishing between propagons and diffusons has remained a challenge, since both are spatially delocalized. Here, we present a new method that quantifies the extent to which a mode's character corresponds to a propagating mode, e.g., exhibits plane wave modulation. This then allows for clear and quantitative distinctions between propagons and diffusons. By resolving this issue quantitatively, one can now automate the classification of modes for any arbitrary material or structure, subject to a single constraint that the atoms must vibrate stably around their respective equilibrium sites. Several example test cases are studied including crystalline silicon and germanium, crystalline silicon with different defect concentrations, as well as amorphous silicon, germanium, and silica.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Particle deposition onto people in a transit venue

Following the release of an aerosolized biological agent in a transit venue, material deposited on waiting passengers and subsequently shed from their clothing may significantly magnify the scope and consequences of such an attack. Published estimates of the relevant particle deposition and resuspension parameters for complex, real-world environments such as a transit facility are non-existent. In this study, measurements of particle deposition velocity onto cotton fabric samples affixed to stationary and walking persons in a large multimodal transit facility were obtained for tracer particle releases carried out as part of a larger study of subway airflows and particulate transport. Deposition velocities onto cotton and wool were also obtained using a novel automated sampling mechanism deployed at locations in the transit facility and throughout the subway. The data revealed higher deposition velocities than have been previously reported for people exposed in test chambers or office environments. Furthermore, the relatively high rates of deposition onto people in a transit venue obtained in this study suggest it is possible that fomite transport by subway and commuter/regional rail passengers could present a significant mechanism for rapidly dispersing a biological agent throughout a metropolitan area and beyond.

59 BASIC BIOLOGICAL SCIENCES↗